How good can databases deal with Netflow data

Transcription

1 How good can databases deal with Netflow data Bachelorarbeit Supervisor: bernhard Inteligent Networks Group (INET) Ernesto Abarca Ortiz

2 OVERVIEW INTRODUCTION METHODOLOGY RESULTS Hardware resource usage Data insertion Data quering CONCLUSIONS FUTURE WORK QUESTIONS 2

3 INTRODUCTION GROWING TRAFFIC Networks and Broadband Access are becoming even faster + Multimedia streaming, social networks, P2P and more users + More applications and protocols are available = More data is generated and crossing our networks Network monitoring and data analysis is more complex 3

4 INTRODUCTION NETFLOW (I) FLOW: Network connection's aggregated data - Time stamp; source/destination for ip, mask, as and port - Flow length in bytes / packets, other info NETFLOW: Protocol for router / switches to send flow data - How? - When? - Where? Src: Wikipedia 4

5 INTRODUCTION NETFLOW (II) POSSIBLE USES: - Traffic statistics - Network Security - Autonomous Systems (AS) routers behaviour NETFLOWS ARE STORED IN BINARY FILES - Vendor specific options/tools - File-based limitations WHAT ABOUT A DATABASE TO STORE NETFLOWS? - But which one? - And how? 5

6 INTRODUCTION DATABASES DATABASE: Organized and structured collection of data DBMS: Complete system to manage databases - Multi-server, backup, security... Data can be encoded/stored in different field formats: - Numeric, text, date/time, raw - And fields can be indexed Mar :12: SQL: Common and independent Structured Query Language TRANSACTION: Multiple SQL orders executed together 6

7 INTRODUCTION CHALLENGES FIELD TYPE? - GENERIC: Only integer types - SPECIFIC: IP Address, Time/Date FIELD INDEXING? - Slow insertions, fast queries - Is it worth? TRANSACTIONS FOR DATA INSERTION? HARDWARE REQUIREMENTS? BOTTLENECKS? 7

8 METHODOLOGY Netflow fields selection, database indexes and query design FLOW-EXPORT tool enhancements: - Support for postgresql & sqlite - Field type conversion - Transaction support - Generate statistics: > Disk I/O usage > Time spent processing flows Hardware monitoring for bottlenecks - MRTG, top, dstat, iostat Optimize hardware / software only if required 8

9 RESULTS RESOURCE USAGE STORAGE REQUIREMENTS: - FLOW-TOOLS binary file: > About 17 Million flows > 1.1 Gbytes - DATABASE: Integer fields NOT INDEXED INDEXED (Max) MySQL 0.9 GB 2.3 GB POSTGRESQL 2.3 GB 5.9 GB SQLITE 1.4 GB 2.9 GB CPU USAGE - BOTTLENECK: No multiprocessor support - Mainly used for index creation or complex queries RAM - Some GB required for index creation and complex queries 9

10 RESULTS DATA INSERTION (I) CONSTANT BEHAVIOUR POSTGRESQL FLUCTUATES AS IT WRITES MORE DATA TO DISK MYSQL IS TWICE FASTER: 14K FLOWS/SEC 10

11 RESULTS DATA INSERTION (II) ON INDEXING, TIME DEPENDS ON AMOUNT OF DATA WRITTEN SQLITE IS NEARLY TWO TIMES SLOWER THAN POSTGRESQL EXTRANGE BEHAVIOUR AT THE END 11

12 RESULTS DATA INSERTION (III) TRANSACTIONS MAKE SQLITE FASTER THAN PGSQL; OTHERS JUST A BIT INDEXING REQUIRES MUCH MORE RESOURCES 12

13 RESULTS DATA QUERY - Flow-tools always require the same execution time - Databases are faster when specific data is requested - Flow-tools are much faster aggregating data - Databases required more than 4 gb of ram There are no big differences when querying Integer or specific fields 13

14 RESULTS DATA DIVERSITY AND SCALABILITY DATA DIVERSITY: Important in index creation and aggregation queries SCALABILITY: Is feasible but can depend on data diversity 14

15 CONCLUSIONS IS IT FEASIBLE TO USE NETFLOW WITH DATABASES? - Yes! - But requires: Twice HDD storage and about 8 GB RAM - Database multiprocessor support is recommendable - Data diversity and traffic pattern can be important for indexing BEST SOLUTION: MySQL - Integer fields - No indexes - Transactions: optional 15

16 FUTURE WORK - DATABASE NORMALIZATION - DATABASE SERVER OPTIMIZATION - COMPARE IT WITH NON SQL DATABASE SYSTEMS 16

17 QUESTIONS Questions? Answer: 42 17